SEARCH · Engineering Papers

Results for “sample preparation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Evaluating inkjet dispenser/liquid vortex capture-mass spectrometry for single-cell metabolomics in Hep G2 steatosis caused by tamoxifen

Single-cell mass spectrometry (MS) is advancing our understanding of metabolic pathways in heterogeneous cell populations; however, many techniques are slow or require disruptive sample preparations. This study evaluated coupling a modified HP D100 single-cell inkjet dispenser with liquid vortex capture-mass spectrometry (D100/LVC-MS). The D100 is a single-cell inkjet dispenser capable of titrating solutions and isolating single cells via disposable cassettes equipped with microfluidic channels and an impedance sensor. The LVC-MS enables high-throughput capture, lysis, and ionization of analytes for mass spectrometric analysis. The D100/LVC-MS system was characterized through titration and single-cell experiments. Propranolol titration demonstrated linearity across a broad concentration range using the D100/LVC-MS system. Additionally, Hep G2 hepatocarcinoma cells and Chlamydomonas reinhardtii algae were used to showcase the D100’s high-throughput or low-buffer-volume single-cell dispensing strategies. The D100/LVC-MS system’s performance was validated by evaluating tamoxifen-induced steatosis in Hep G2 cells. Tamoxifen, associated with nonalcoholic fatty liver disease in breast cancer patients following long-term use, was tested in Hep G2 cells at 20 µM for 72 h against DMSO-treated controls. High-throughput analysis of 500 cells per condition, completed in 25 min per run, demonstrated the system’s efficiency. The D100/LVC-MS system simultaneously quantified tamoxifen and measured triglycerides and phosphatidylcholines. Triglycerides were upregulated in the tamoxifen-treated cells and the results indicated two distinct cell populations, differing in tamoxifen and phosphatidylcholines levels, suggesting heterogeneity within the treated population. In conclusion, these findings highlight the D100/LVC-MS system as a cost-effective, high-throughput platform for single-cell metabolomics and lipidomics, with significant potential for evaluating metabolic alterations.

Chromatography↗

DOE OSTI2022

Total Mercury Analysis of Radioactive Waste Containing Multiple Mercury Species

In this work, a direct mercury analyzer (DMA) was used to analyze total mercury in radioactive waste samples containing methylmercury and other forms of mercury including Hg o (elemental) together with inorganic ionic mercury species and complexes. These samples were also analyzed using Cold Vapor Atomic Absorption Spectroscopy (CVAAS) and/or Inductively Coupled Plasma Mass Spectroscopy (ICMS). Comparative statistical evaluation of the results from spike solutions/simulants, liquid radioactive waste samples, and interlaboratory performance test samples demonstrated that the various methods generated accurate and/or equivalent total mercury data and equivalent precision (2σ ± < 20%). Triplicate total mercury analysis of an exemplar radioactive waste resulted in an average value of 54.1 mg/L (as Hg) using CVAAS, 55.1 mg/L using ICPMS and 56.0 mg/L using DMA. A primary advantage of the DMA in a radioactive environment is avoiding multi-step, labor-intensive, time-consuming and waste-producing sample preparation protocols needed for CVAAS and ICPMS. DMA was determined to be the preferred method for measuring total mercury in the Savannah River National Laboratory (SRNL) radioanalytical laboratory based on analytical performance combined with ease of use in a radiological containment unit.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2025

Sample screening of uranium ore concentrates using portable spectrophotometers: investigating the correlation between visible colors and chemical signatures

A research collaboration between the Japan Atomic Energy Agency and the Department of Energy’s National Nuclear Security Administration examined nuclear forensic signatures and analytical methods for tracing the origins of uranium ore concentrates (UOCs). Here, this study focuses on utilizing portable spectrophotometers capable of reflectance measurements in the visible light spectrum as a potential rapid screening tool for nuclear forensics analysis. Unlike laboratory-based near-infrared spectroscopy or digital image analysis, this research investigated the potential to correlate visible color measurements with key nuclear forensics signatures using seven types of UOC samples with known origins and three UOC certified reference materials. Results demonstrated that distinct color groups, quantified using CIELAB values, correlated with major uranium compounds. Furthermore, the findings indicated that trace elements can influence the UOC colors, providing additional insights into material characteristics. Although this approach requires further validation across a broader range of UOC species, this study demonstrated that simple colorimetric analysis using visible spectrophotometry, which does not require complex sample preparation or data processing, can serve as a practical and novel rapid tool for preliminary screening and attribution in nuclear forensics investigations.

and nuclear chemistry↗

DOE OSTI2025

Interlaboratory comparison of secondary ion mass spectrometry analysis results from the 7th international technical nuclear forensics working group collaborative material exercise

A review and interlaboratory comparison of secondary ion mass spectrometry (SIMS) data obtained by laboratories participating in the International Technical Nuclear Forensics Working Group (ITWG) 7th Collaborative Material Exercise (CMX-7) has been conducted. The analyzed materials were two uranium compounds in powder form and two pieces of uranium metal. The instruments used in this comparison were a small-geometry (SG) SIMS, CAMECA IMS 7f from the Research Centre Rez, and a large-geometry (LG) SIMS, CAMECA IMS 1280 from Los Alamos National Laboratory. Despite the differences in instruments and analytical procedures, e.g., sample preparation, SIMS setups, and data post-processing, there was good agreement for the 234 U/ 238 U, 235 U/ 238 U, and 236 U/ 238 U ratios in the analyzed materials. The main difference was in the precision, which was, as expected, higher for the LG-SIMS. In addition, a comparison between the laboratories was also made for the image processing algorithms applied to raw data acquired in automated particle measurement (APM) mode. In conclusion, the result of this comparison has led to identification of best practices for setting up parameters of the APM software.

and nuclear chemistry↗

DOE OSTI2020

High-Energy X-ray Tomographic Analysis of Precursor Metal Powders (Ti-6Al-4V) Used for Additive Manufacturing

We utilized high-energy x-ray tomography to characterize Ti-6Al-4V metal powders (both as-received and recycled) used in powder-bed additive manufacturing process. The image processing workflow was developed to process and analyze large amount of data objectively by computer program. The distribution of size and shape of the metal particles as well as defect (mainly porosity) inside the particles was analyzed with the statistical representation and resolution in micrometer. The result revealed that circular-shaped porosity with various sizes could be embedded in the powder particles. These porosities could potentially be transferred to the 3D printed part and critically affect the mechanical performance of the component. The present study shows the effectiveness of characterizing metal powders using x-ray imaging techniques where sufficient number of particles can be sampled within tens of minutes with a minimum sample preparation and high accuracy. Clear structural differences in the as-received and recycled powders were delineated that helps in determining the feasibility of using the recycled powders.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Review: Recent advances of ToF-SIMS for environmental analysis and imaging

Background: Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a powerful surface analysis technique, initially developed and applied in inorganic materials and semiconductors. In past decades, ToF-SIMS has attracted more attention in its analysis capabilities of organic materials, with increased applications in biology, medical, and health development. It has also become a versatile and effective tool in environmental analysis due to its high mass resolution, mass accuracy, and depth profiling. Results: In this review, we first give an overview of the principle of ToF-SIMS and follow with recent ToF-SIMS applications in exemplary environmental study cases, including atmospheric aerosol, soil, water, plant, and organic solvent analysis. Moreover, sample preparation techniques are summarized in relation to corresponding environmental applications. Specifically, we call attention to ToF-SIMS investigations showcasing studies in surface chemical compositions, images, and depth profile analysis. These findings emphasize the important role of interfacial chemistry in environmental processes and provide valuable insights into dynamic processes, such as chemical transformation, particle formation, plant biology, and microbial inspired biotechnology development. The mass spectral imaging results acquired by ToF-SIMS offer a deeper understanding of intermediate stages and transient phases for environmental specimens. Significance: In situ and operando imaging offer new possibilities in studying phenomena in real time with high spatial resolution. Furthermore, it is anticipated that more research groups will use ToF-SIMS in environmental research given recent advances in measurement capabilities and surging needs in chemical mapping of complex analytes and systems.

Aerosol↗

DOE OSTI2025

Near-infrared spectroscopy as a green analytical tool for sustainable biomass characterization for biofuels and bioproducts: An overview

Biomass, a widely used renewable energy source, requires characterization to optimize biofuel and bioproduct processes, customize feedstocks, and ensure economic and environmental sustainability. Conventional wet-chemistry methods for biomass analysis are slow, expensive, and require significant reagents and skilled personnel. In contrast, near-infrared (NIR) spectroscopy, a faster, cost-effective, and reagent-free green technology, enables non-destructive biomass analysis with minimal sample preparation. This study provides an overview of the fundamentals of NIR spectroscopy and explores its recent applications for analyzing various biomass properties important to the biofuel and bioproduct industry. The study also critically evaluates the challenges and opportunities of using NIR spectroscopy for biomass analysis. This review aims to guide future research for rapid and high throughput characterization of biomass in the biomass industry, supporting the United Nations’ sustainable development goal (SDG) 7: producing affordable and sustainable energy.

Biofuels↗

DOE OSTI2026

Mechanochemical synthesis of hydraulically reactive calcium silicate minerals via thermally-assisted mechanical grinding

This study explores a thermally assisted mechanochemical approach alternative to conventional cement synthesis as a potential to produce hydraulically reactive calcium silicate phases. Ball milling of mixed CaO/SiO 2 feedstocks at temperature ranges 100-300 °C increases the formation of the Ca-O-Si bonds and precursor reactivity. Spectroscopic analyses (FTIR, MAS-NMR, UV-Vis DRS) indicate increasing amorphization with milling temperature, attributed to improved mixing and thermally assisted diffusion. Upon hydration, all treated samples exhibit exothermic heat release, with the sample prepared at 300 °C showing the most pronounced reactivity. Thermal analysis reveals weight loss consistent with C-S-H formation, confirming cement-like behavior. In summary, moderate thermal input during milling promotes structural activation and enhances downstream hydraulic reactivity, providing a proof-of-concept for energy-reduced cement precursor processing.

Alite↗

DOE OSTI2023

Bending and shear improvements in 3D-printed core sandwich composites through modification of resin uptake in the skin/core interphase region

Fused deposition modeling (FDM) printed polymers are rarely used as a structural material due to anisotropic and low mechanical properties compared with conventional composites. In recent years, greater need has been expressed for recycling of materials, such as recyclable FDM, at the end of service life to reduce environmental pollution and manufacture cost. However, how the amount of resin uptake in the skin and skin/core interphase affects the bending and shear performance of the sandwich composites when replacing the low strength and ductile core (conventional core) with a high strength and brittle core (FDM printed PLA (polylactic acid) core) still remains unclear. A new manufacturing routine is needed to improve the incorporation of FDM printed polymers in composite structures. In this work, FDM printed PLA was used as core material and sandwiched between two unidirectional glass fiber reinforced polymer (GFRP) skins to form a sandwich composite by compression-molding (CM) process, which provides a good manufacturing strategy for skin/core interphase modification. The significance of the CM process is proved by investigating the effect of resin uptake on bending and in-plane/out-of-plane shear performances. Current first order shear deformation (FSDT) theory lacks a direct connection between the in-plane shear stress and out-of-shear stress in the core region of sandwich composites. With the help of DIC, a connection between the in-plane shear and the out-of-plane shear strain was built and in-plane shear properties can acquire through out-of-plane shear properties, hence reducing the redundancy of sample preparation or the need for simulation. A significant improvement was found compared with the optimized resin uptake (Optimized resin uptake range: 20.43%–22.86 wt%) 3D-printed PLA core sandwich composite and lowest performance sandwich composite (Improvement: in-plane shear strength (~34%)/modulus (~29%), out-of-plane shear strength (~25%)/modulus (~31%), specific peak bending load (~19%)). Finally, compared with balsa core sandwich composites, the 3D-printed cores are suitable for use in composite sandwich structures in many applications with a satisfactory strength-to-weight ratio.

3D-printed core sandwich composite↗

DOE OSTI2022

A machine learning approach to determine the elastic properties of printed fiber-reinforced polymers

This work focuses on the simultaneous determination of the elastic constants and the fiber orientation state for a short fiber-reinforced polymer composite by performing a minimum of experimental tests. Here we introduce a methodology that enables the inverse determination of fiber orientation state and the in-situ polymer properties by performing tensile tests at the composite coupon level. We demonstrate the approach for the extrusion deposition additive manufacturing (EDAM) process to illustrate one application of the methodology, but the development is such that it can be applied to short fiber-reinforced polymer (SFRP) systems processed via other methods. Currently, developing composites additive manufacturing digital twins require extensive material characterization. In particular, the mechanical characterization of the orthotropic elastic properties of a composite involves extensive sample preparation and testing, therefore the elasticity tensor is generally populated using a micromechanics model. This, however, requires measuring the fiber orientation state in addition to knowing the constituent material properties. Experimentally measuring the fiber orientation state can be tedious and time consuming. Further, optical methods are limited to resolving the orientation of cylindrical fibers or cluster of non-cylindrical fibers, and computed tomography (CT) methods scan regions of volume that are much smaller than a full printed bead. Therefore, we propose a methodology, accelerated by machine learning, to identify the anisotropic mechanical properties and fiber orientation state at the same time. Early results show that inference of the fiber orientation and composite properties is possible with as few as three tensile tests. Our results show that a combination of the choice of the micromechanics model and reliable set of experiments can yield the nine elastic constants, as well as, the fiber orientation state.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Machine learning in nuclear materials research

Nuclear materials are often demanded to function for extended time in extreme environments, including high radiation fluxes with associated transmutations, high temperature and temperature gradients, mechanical stresses, and corrosive coolants. They also have a wide range of microstructural and chemical makeups, resulting in multifaceted and often out-of-equilibrium interactions. Machine learning (ML) is increasingly being used to tackle these complex time-dependent interactions and aid researchers in developing models and making predictions, sometimes with better accuracy than traditional modeling that focuses on one or two parameters at a time. Conventional practices of acquiring new experimental data in nuclear materials research are often slow and expensive, limiting the opportunity for data-centric ML, but new methods are changing that paradigm. Here we review high-throughput computational and experimental data approaches, especially robotic experimentation and active learning that is based on Gaussian process and Bayesian optimization. We show ML examples in structural materials (e.g., reactor pressure vessel (RPV) alloys and radiation detecting scintillating materials) and highlight new techniques of high-throughput sample preparation and characterizations, and automated radiation/environmental exposures and real-time online diagnostics. Herein, this review suggests that ML models of material constitutive relations in plasticity, damage, and even electronic and optical responses to radiation are likely to become powerful tools as they develop. Finally, we speculate on how the recent trends of using natural language processing (NLP) to aid the collection and analysis of literature data, interpretable artificial intelligence (AI), and the use of streamlined scripting, database, workflow management, and cloud computing platforms that will soon make the utilization of ML techniques as commonplace as the spreadsheet curve-fitting practices of today.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Zn uptake by illite and argillaceous rocks

The uptake of Zn by Illite du Puy (IdP) and two argillaceous rocks, Opalinus Clay (OPA) and Boda Claystone (BODA) was investigated. The uptake of Zn by illite was studied in 0.1 M NaCl at near-neutral pH and Zn loadings varying from 2.1 to 42 mmol/kg. The Zn uptake by the two argillaceous rock systems was carried out in 0.1 M NaCl at pH 7.2 and in their respective porewaters at pH 8.0 to evaluate the influence of porewater composition. The Zn loadings varied from 1.8 to 86 mmol/kg and 1.7 to 60 mmol/kg for OPA and BODA, respectively. The simplified “bottom-up approach” to predict the uptake of Zn to natural rocks with different clay mineral contents and porewater compositions was tested. This approach was found to be applicable in the argillaceous rock systems at low Zn equilibrium ([Zn] eql ) concentrations below 10 -7 M. However, at [Zn]eql above 10 -7 M, the model calculations clearly underpredicted the sorption data. The extended X-ray absorption fine structure (EXAFS) results support findings based on wet chemistry calculations using the 2 site protolysis non-electrostatic surface complexation and cation exchange (2SPNE SC/CE) sorption model. In the IdP system with prolonged reaction times of up to two years, formation of Zn precipitates was not observed. This indicates that the Zn surface complexes are stable over a time period of two years, and dissolution and recrystallization processes might not play a significant role in the Zn-IdP uptake process. In addition, the EXAFS results on illite corroborate previous findings on the existence of weak and strong sites types in dioctahedral clay minerals, as assumed in the 2SPNE SC/CE model. In the OPA and BODA systems, precipitation processes could start to begin at metal loadings of 16 mmol/kg and 24 mmol/kg, respectively. The differences between argillaceous rock samples prepared in NaCl and porewater are modest indicating that in the case of Zn the clay minerals play a predominant role in the uptake process, and that the effects originating from the porewater are minor. Furthermore, despite the differences in mineralogy, both argillaceous rocks show the same uptake behaviour, indicating that the clay minerals are predominantly responsible for the sorption at low and the precipitation processes at higher Zn concentrations. The study demonstrates how results on “pure” systems such as IdP can be transferred to predict the uptake by argillaceous rocks at low sorbate concentrations.

58 GEOSCIENCES↗

DOE OSTI2020

X-Ray Fluorescence Microscopy: A Method of Measuring Ion Concentrations in the Ear

This technical note describes synchrotron x-ray fluorescence microscopy (XFM) as a method for measuring the concentrations of various elements in cross-sections of the ear at extremely high resolution. This method could be of great importance for addressing many open questions in hearing research. XFM uses synchrotron radiation to evoke emissions from many biologically relevant elements in the tissue. The intensity and wavelength of the emitted radiation provide a fingerprint of the tissue composition that can be used to measure the concentration of the elements in the sampled location. Here, we focus on energies that target biologically-relevant elements of the periodic table between magnesium and zinc. Since a highly focused x-ray beam is used, the spot size is well below 1 mu m and the samples can be scanned at a nanometer lateral resolution. This study shows that measurement of the concentrations of different elements is possible in a mid-modiolar cross-section of a mouse cochlea. Images are presented that indicate potassium and chloride "hot spots" in the spiral ligament and the spiral limbus, providing experimental evidence for the potassium recycling pathway and showing the cochlear structures involved. Scans of a section obtained from the incus, one of the middle ear ossicles, in a developing mouse have shown that zinc is not uniformly distributed This supports the hypothesis that zinc plays a special role in the process of ossification. Although limited by sophisticated sample preparation and sectioning, the method provides ample exciting opportunities, to understand the role of genetics and epigenetics on hearing mechanisms in ontogeny and phylogeny.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Thermal conductivity measurement using modulated photothermal radiometry for nitrate and chloride molten salts

Molten salts are being used or explored for thermal energy storage and conversion systems in concentrating solar power and nuclear power plants. Thermal conductivity of molten salts is an important thermophysical property dictating the performance and cost of these systems, but its accurate measurement has been challenging, as evidenced by wide scattering of existing data in literature. The corrosive and conducting nature of these fluids also leads to time consuming sample preparation processes of many contact-based measurements. Here, in this work, we report the measurement of thermal conductivity of molten salts using a modulated photothermal radiometry (MPR) technique, which is a laser-based, non-contact, frequency-domain method adopted for molten salts for the first time. By unitizing the advantages of front side sensing of frequency-domain measurements and the vertical holder orientation, the technique can minimize the natural convection and salt creeping effects, thus yielding accurate molten salt thermal conductivity . The MPR technique is first calibrated using standard molten materials including paraffin wax and sulfur. It is then applied on measuring pure nitrate salts (NaNO 3 and KNO 3 ), solar salt (NaNO 3 –KNO 3 mixture), and chloride salt (NaCl–KCl–MgCl 2 ). The measurement results are compared with data from literature, especially those obtained from laser flash analysis (LFA). Our results demonstrate that the MPR is a convenient and reliable technique of measuring thermal conductivity of molten salts. Accurate thermal conductivity data of molten salts will be valuable in developing the next-generation high-temperature thermal energy storage and conversion systems.

14 SOLAR ENERGY↗

DOE OSTI2022

RAPID UNSEPARATED RARE EARTH ELEMENT ANALYSES BY ISOTOPE DILUTION MULTICOLLECTOR INDUCTIVELY COUPLED MASS SPECTROMETRY (ID-MC-ICP-MS)

We present a method for analyzing rare earth elements (REEs) by isotope dilution without separation of individual elements. Utilizing a Nu Plasma 2 multicollector inductively coupled plasma mass spectrometer (MC-ICP-MS) equipped with an Aridus II desolvation nebulizer, sample introduction tuning parameters (torch position, gas flows) were investigated and used to minimize oxide formation (e.g., NdO/Nd <0.05%) and remove the need to analyze the REEs as separated “cuts.” Ratios for spike/sample isotopes in mixed synthetic standards containing varying amounts of Ce, Nd, Sm, Eu, Gd, Dy, Er, and Yb were measured accurately within 1% of IUPAC values. La and Lu in the standards were more than 2% off from expected values due to more demanding interference corrections. A USGS BCR-2 rock standard was also processed with flux fusion, iron coprecipitation and a single column pass bulk separation followed by analysis. The concentrations for Ce, Nd, Sm, Eu, Dy, Er, and Yb fell within 2% of consensus values. A United States Geological Survey (USGS) BIR-1A rock standard was also processed in triplicate by hydrofluoric and nitric acid digestion, yielding rare earth concentrations within 3% of consensus values with 0.3% relative standard deviation (n=3). This demonstrates the ability to produce high quality REE patterns of comparable quality to traditional methods involving labor and time intensive REE separation, with sample preparation and analytical times that are comparable to analyses against isotope dilution by single-collector ICP-MS.

Shen, Steve D.↗

DOE OSTI2020

A scalable approach of using biomass derived glycerol to synthesize cathode materials for lithium-ion batteries

Glycerol, a main byproduct of biodiesel, was used as the fuel agent in a scalable flame-assisted spray pyrolysis approach to synthesize micron-size cathode materials. Single droplet combustion, particle morphology, and electrochemical performance were examined considering the effects of salt concentration, water addition, and post-annealing time on synthesizing Li(Ni 1/3 Co 1/3 Mn 1/3 )O 2 (NCM111) cathode materials. Single droplet tests showed that a sufficient amount of water in the glycerol-based precursor could delay droplet inflation and ignition. Moreover, using a two-fluid atomization nozzle, spray tests demonstrated that adding water would result in less wrinkled and more uniform particles. Nevertheless, increasing water proportion in the precursor could reduce the reaction heat, resulting in that samples prepared with water addition needed longer post-annealing time to improve their electrochemical performance. Using the precursor without water, the best performed NCM111 cathode material was synthesized with only 2 h of post-annealing. It has a discharge capacity of 163.3 mAh/g at 0.1C and 85.5% capacity retention at 1C after 100 cycles. Furthermore, the current work confirmed the capability of using glycerol as a sustainable fuel agent to synthesize NCM111 cathode materials, and also provided basic conditions for the development of large-scale production in the future.

25 ENERGY STORAGE↗

DOE OSTI2023

Core-scale numerical simulation and comparison of breakdown of shale and resulting fractures using sc-CO 2 and water as injectants

Supercritical carbon dioxide (sc-CO 2 ) is an alternative to water for stimulation of low permeability systems such as shale gas and geothermal resources. Previously core-scale experimental studies have compared the behavior of CO 2 to water injection for sample breakdown. Due to differences in experimental setup and core sample preparation, inconsistent or even apparently contradictory conclusions have resulted. To reconcile this contradiction, a phase-field numerical model is applied to understand hydraulic fracturing experiments using Green River shale found in the literature. The finite element numerical model incorporates a rate-dependent phase-field fracture model developed separately to describe fracture initiation and growth. We investigate the impact of various material and fluid properties on the resulting fractures. Most importantly, we study the effect of fluid properties and boundary conditions on the breakdown pressure, including the direction of the resulting fracture plane. Model results predict that (1) sc-CO 2 injection in the laboratory may result in greater breakdown pressure than that of water under no-flow boundary conditions because lower viscosity sc-CO 2 may result in pressure build up at the core boundary that opposes fracture initiation and (2) lower viscosity sc-CO 2 also produces fast-propagating fractures that are less influenced by the bedding plane on their resulting fracture topology. Here our model offers a straightforward explanation and reconciliation of existing experimental observations, as well as a means to extrapolate to new conditions. Exploration of field-scale conditions suggests less pronounced or no elevation in breakdown pressure when sc-CO 2 is injected because the pressure build up effect at the system boundary is significantly less or absent at field length scales.

42 ENGINEERING↗

DOE OSTI2020

Predicting boron coordination in multicomponent borate and borosilicate glasses using analytical models and machine learning

Accurate prediction of boron coordination in multicomponent glasses is critical in glass science and technology as it strongly affects the properties of borate and borosilicate glasses. We have collected a dataset containing 657 glasses from literature with boron coordination values and developed models using analytical functions based on the well accepted Dell, Xiao and Bray model. Good prediction of boron coordination with a R 2 value higher than 0.8 was obtained. The large variation of boron coordination from experiments, originated from sample preparations and characterizations, led to difficulties in obtaining models with better prediction performance. Various machine learning (ML) algorithms were evaluated and slightly better prediction performance was observed; however, interpretation of the ML models is less straight forward. In conclusion, this study developed various models capable of providing quantitative boron coordination predictions, providing insights into its structural roles in multi-component glasses, and suggesting fruitful areas for future research.

36 MATERIALS SCIENCE↗